Krishna Rajan

City University of Hong Kong — Hong Kong

Engineering · Physical Sciences

36h-index5.1kcitations251works2.62yr avg
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Research Topics

Advanced Materials Characterization Techniques(46), Machine Learning in Materials Science(45), Hydrogen embrittlement and corrosion behaviors in metals(19), Metal and Thin Film Mechanics(16), Computational Drug Discovery Methods(15)

Publications251 total

Benchmarking of Molecular Fingerprints for PFAS molecules
2025Open Access
Interfaces at the nano scale: general discussion
Faraday Discussions·2025
Interfaces at the micron scale: general discussion
Faraday Discussions·2025
Connecting length scales: general discussion
Faraday Discussions·2025
Graph-Based Data Analysis for Building Chemistry–Phase Design Rules for High Entropy Alloys
Crystals·2024· 1 citedOpen Access
Anisotropic mechanical behavior of cesium tin iodide perovskite subjected to uniaxial tension
Physical Review Materials·2024
An artificial intelligence platform for automated PFAS subgroup classification: A discovery tool for PFAS screening
The Science of The Total Environment·2024· 17 cited
Molecular dynamics study of mechanical deformation in cesium lead halide perovskites
Physical Review Materials·2023· 3 cited
An Artificial Intelligence Platform for Automated PFAS Subgroup Classification: A Discovery Tool for PFAS Screening
2023· 3 citedOpen Access
Strain-induced anisotropic ion migration in single-crystal cesium lead halide perovskites
Journal of Applied Physics·2023· 9 cited
Introduction to Materials Informatics
Materials Advances·2023· 4 citedOpen Access
Machine-learning-based intelligent framework for discovering refractory high-entropy alloys with improved high-temperature yield strength
npj Computational Materials·2022Open Access
Machine-Learning-Based Intelligent Framework for Discovering Refractory High-Entropy Alloys with Improved High-Temperature Yield Strength
Research Square (Research Square)·2022· 2 citedOpen Access
Artificial intelligence informed toxicity screening of amine chemistries used in the synthesis of hybrid <scp>organic–inorganic</scp> perovskites
AIChE Journal·2022· 3 cited
New Generalized Informatics Framework for Development of Large Scale Virtual Battery Material Databases
arXiv (Cornell University)·2022Open Access
High-Throughput Computation of Li-based Battery Material Databases: Chemistry-Processing-Property Relationships
arXiv (Cornell University)·2022Open Access
Machine-Learning-Based Intelligent Framework for Discovering Refractory High-Entropy Alloys with Improved High-Temperature Yield Strength
arXiv (Cornell University)·2021· 5 citedOpen Access
Quantum signatures for screening metavalent solids
The Journal of Chemical Physics·2021· 11 cited
Designing a Periodic Table for Alloy Design: Harnessing Machine Learning to Navigate a Multiscale Information Space
JOM·2020· 6 cited
A Database Framework for Rapid Screening of Structure-Function Relationships in PFAS Chemistry
2020Open Access
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Frequent Co-authors

Scott Broderick(7), Changwon Suh(5), Mahendra K. Sunkara(3), Susan B. Sinnott(3), Ruifeng Zhang(3), Long‐Qing Chen(2), Patricio F. Méndez(2), Jacek B. Jasiński(2), Madhu Menon(2), W.E. Wallace(2), Paul A.J. Bagot(2), Simon P. Ringer(2), Arun Rajagopalan(2), Srikant Srinivasan(2), K. G. Wang(2), M. E. Glicksman(2), Chang Kong(2), Wei Hu(2), Xiaoli Tan(2), Juan Pablo(1)